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function p = pdf(m, v, x) %计算多元高斯密度函数 %输入: % m -- 均值向量, SIZE*1 % v -- 方差向量, SIZE*1 % x -- 输入向量, SIZE*1 %输出: % p -- 输出概率 p = (2 * pi * prod(v)) ^ -0.5 * exp(-0.5 * (x-m) ./ v * (x-m)');

%程序是正确的,但泛化能力差 clc; clear; t1=cputime; num=10; disp('正在计算数字识别PNN模型...') for i=1:num fname = sprintf('..\\digit\\%da.wav',i-1); x = wavread(fname); [x1 x2] = vad(x); m = mfcc(x); m = m(

function ccc = mfcc(x) % 归一化mel滤波器组系数 bank=melbankm(24,256,8000,0,0.5,'m'); bank=full(bank); bank=bank/max(bank(:)); % DCT系数,12*24 for k=1:12 n=0:23; dctcoef(k,:)=cos((2*n+1)*k*pi/(2*24)

/* SDLMain.m - main entry point for our Cocoa-ized SDL app Initial Version: Darrell Walisser Non-NIB-Code & other changes: Max Horn Feel

/* SDLMain.m - main entry point for our Cocoa-ized SDL app Darrell Walisser - dwaliss1@purdue.edu Feel free to customize this file to suit your needs */ #import "SDL.h" #import "

function [gaborp_2d]=gabor2d_sub(angle,num_disk) % Modified by PRTsinghua@hotmail.com variance=32; k=10; x=cos(angle*pi/num_disk); y=sin(angle*pi/num_disk); w=(2*pi)/k; p=0; m=0; for (i

function [CroppedPrint] = cropping(XofCenter,YofCenter,CentralizedPrint) % Modified by PRTsinghua@hotmail.com N = 175; M=size(CentralizedPrint,1); imgN=size(CentralizedPrint,1); imgM=size(Cen

function [disk,vector] = sector_norm( image , mode , mix) % Modified by PRTsinghua@hotmail.com % N=175 size of cropped image (175 x 175) N=175; % Number of sectors M=38; size_m=N*N; mea

[I,map]=imread('blood1.tif'); imshow(I,map); H2=[-1 -1 -1;-1 -9 -1;-1 -1 -1]; J1=filter2(H2,I); % 高通滤波 figure,imshow(J1,map); I=double(I); M=[1 1 1;1 1 1;1 1 1]/9; J2=filter2(M,I)

I=imread('blood1.tif'); imshow(I); f=double(I); % 数据类型转换，MATLAB不支持图像的无符号整型的计算 g=fft2(f); % 傅立叶变换 g=fftshift(g); % 转换数据矩阵 [M,N]=size(g); nn=2; % 二阶巴特沃斯(Butterworth)高通滤波器